iDeer: A decision-support tool for managing deer alongside woodland creation

Amy Gresham , Matthew Grainger, Matt Guy, Chloe Bellamy, Andrew Rattey, Graeme Shannon, Freya A. V. St John, Alastair I Ward, Elena Cini, Felix Eigenbrod, Owain Barton, Robin Gill, Chris Hirst, David Hooton, David Jam, Jochen Langbein, Peter John Lawrence, Thomas W Logan, Ewan McHenry, Chris Nichols, Paul Orsi, Rory Putman, Arman Siddiqui, Eilidh M. W. Smith, Rebecca Spake

Increasing deer (Cervidae) densities driven by land-use change and climate warming represent a growing challenge to the establishment and management of woodlands across temperate biomes. Targeting deer management is challenging without spatially explicit information on potential impact risks under alternative management scenarios. Here we present the iDeer Tool (https://ideer-project.shinyapps.io/ideer/), an interactive decision-support tool for predicting deer impact risk to woodlands across England and Wales. We present the Tool’s underlying spatially explicit Bayesian Belief Network models. Through iterative expert elicitation, we co-developed influence diagram structures and conditional probability tables, then validated spatial predictions across multiple landscapes. The model structures incorporate landscape-scale influences on key ecological processes related to deer energy acquisition and loss, and associated habitat requirements for nutritional resources and shelter. The tool enables users to view current deer impact risk maps for large-bodied and small-bodied deer species and assess how different woodland establishment scenarios may alter the distribution of impact risk across landscapes, beyond the immediate planting sites. The tool facilitates pre-emptive, collaborative action among landowners by providing risk maps for integration into management plans and grant applications. Our replicable framework can be adapted to develop similar decision support tools for different species, countries, and land-use management challenges.